4 citations · 4 across the 15 of their papers we have counts for
9 papers · 1 filter
How Far Are We from Removing the Visual Encoder? Scaling Laws for Encoder-Free Multimodal Pretraining
Lin Chen, Bolin Ni, Qi Yang +6
Most modern multimodal large language models (MLLMs) build on a pretrained visual encoder that provides a strong visual prior. Encoder-free MLLMs instead learn visual representatio…
Dr.Credit: Rubric-Grounded Process Credit Assignment for Deep Research Agents
Yingjian Zhu, Zhenyi Wang, Jiaxin Guo +6
Rubric-based tasks are increasingly addressed through reinforcement learning (RL), with rubric scores used as training rewards. However, these rewards typically supervise final ans…
DICS: Exploring Data Intrinsic Consistency for Visual Instruction Selection
Yuyang Hong, Jinhui Guo, Jiaqi Gu +6
Visual instruction tuning is crucial for advancing the vision-language alignment and instruction-following capabilities of Vision-Language Models (VLMs). However, identifying optim…
DiffPDE: Masked Diffusion Language Models as PDE Solver
Wenxuan Guo, Yuyang Hong, Lubin Fan +4
Existing approaches for synthesizing Partial Differential Equation (PDE) solvers predominantly rely on autoregressive models, yet their global left-to-right decoding incurs substan…
Joint Training of Multi-Token Prediction in Reinforcement Learning via Optimal Coefficient Calibration
Zili Wang, Jiajun Chai, Lin Chen +3
Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as the standard paradigm for improving reasoning capability of large language models, while Multi-Token Prediction…
WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering
Yingjian Zhu, Xinming Wang, Kun Ding +3
Multi-modal Retrieval-Augmented Generation (RAG) has emerged as a highly effective paradigm for Knowledge-Based Visual Question Answering (KB-VQA). Despite recent advancements, pre…
VisBrowse-Bench: Benchmarking Visual-Native Search for Multimodal Browsing Agents
Zhengbo Zhang, Jinbo Su, Zhaowen Zhou +14
The rapid advancement of Multimodal Large Language Models (MLLMs) has enabled browsing agents to acquire and reason over multimodal information in the real world. But existing benc…
Beyond Sequential Distance: Inter-Modal Distance Invariant Position Encoding
Lin Chen, Bolin Ni, Qi Yang +5
Despite the remarkable capabilities of Multimodal Large Language Models (MLLMs), they still suffer from visual fading in long-context scenarios. Specifically, the attention to visu…
CC-VQA: Conflict- and Correlation-Aware Method for Mitigating Knowledge Conflict in Knowledge-Based Visual Question Answering
Yuyang Hong, Jiaqi Gu, Yujin Lou +7
Knowledge-based visual question answering (KB-VQA) demonstrates significant potential for handling knowledge-intensive tasks. However, conflicts arise between static parametric kno…